diff --git a/paddle/framework/operator.h b/paddle/framework/operator.h
index 9874a7c295d07601cffc776c24f5334df1d8c83a..29fa3ffd87fb50a4f3056581921c1792f0ec21f2 100644
--- a/paddle/framework/operator.h
+++ b/paddle/framework/operator.h
@@ -233,6 +233,11 @@ class InferShapeContext {
 
   const Scope& scope() const { return scope_; }
 
+  template <typename T>
+  inline const T& GetAttr(const std::string& name) const {
+    return op_.GetAttr<T>(name);
+  }
+
   size_t InputSize(const std::string& name) const {
     return op_.Inputs(name).size();
   }
diff --git a/paddle/operators/gaussian_random_op.cc b/paddle/operators/gaussian_random_op.cc
index 9eb976fed1719f1bb5e51cb38dd4052153fe6851..056447901d418355c01d499f7d92d0b59a39edfa 100644
--- a/paddle/operators/gaussian_random_op.cc
+++ b/paddle/operators/gaussian_random_op.cc
@@ -19,13 +19,12 @@ template <typename T>
 class CPUGaussianRandomKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
-    float mean = context.op().GetAttr<float>("mean");
-    float std = context.op().GetAttr<float>("std");
+    float mean = context.GetAttr<float>("mean");
+    float std = context.GetAttr<float>("std");
     auto* tensor = context.Output<framework::Tensor>("Out");
     T* data = tensor->mutable_data<T>(context.GetPlace());
 
-    unsigned int seed =
-        static_cast<unsigned int>(context.op().GetAttr<int>("seed"));
+    unsigned int seed = static_cast<unsigned int>(context.GetAttr<int>("seed"));
     std::minstd_rand engine;
     if (seed == 0) {
       seed = std::random_device()();
diff --git a/paddle/operators/gaussian_random_op.cu b/paddle/operators/gaussian_random_op.cu
index 9769fbcd2be91322fafea15676b987b052003ffd..833a82bbf293a0892531283dc681ca2edd72f6a1 100644
--- a/paddle/operators/gaussian_random_op.cu
+++ b/paddle/operators/gaussian_random_op.cu
@@ -42,14 +42,13 @@ class GPUGaussianRandomKernel : public framework::OpKernel {
   void Compute(const framework::ExecutionContext& context) const override {
     auto* tensor = context.Output<framework::Tensor>("Out");
     T* data = tensor->mutable_data<T>(context.GetPlace());
-    unsigned int seed =
-        static_cast<unsigned int>(context.op().GetAttr<int>("seed"));
+    unsigned int seed = static_cast<unsigned int>(context.GetAttr<int>("seed"));
     if (seed == 0) {
       std::random_device rd;
       seed = rd();
     }
-    T mean = static_cast<T>(context.op().GetAttr<float>("mean"));
-    T std = static_cast<T>(context.op().GetAttr<float>("std"));
+    T mean = static_cast<T>(context.GetAttr<float>("mean"));
+    T std = static_cast<T>(context.GetAttr<float>("std"));
     thrust::counting_iterator<unsigned int> index_sequence_begin(0);
     ssize_t N = framework::product(tensor->dims());
     thrust::transform(index_sequence_begin, index_sequence_begin + N,
diff --git a/paddle/operators/scale_op.h b/paddle/operators/scale_op.h
index 760b26f5e9ab132be5039ea9edafe9517f357261..65fb77eefad812fa52ac053b791ba1b8f480375f 100644
--- a/paddle/operators/scale_op.h
+++ b/paddle/operators/scale_op.h
@@ -27,7 +27,7 @@ class ScaleKernel : public framework::OpKernel {
     auto* in = context.Input<framework::Tensor>("X");
     tensor->mutable_data<T>(in->place());
 
-    auto scale = static_cast<T>(context.op().GetAttr<AttrType>("scale"));
+    auto scale = static_cast<T>(context.GetAttr<AttrType>("scale"));
 
     auto eigen_out = framework::EigenVector<T>::Flatten(*tensor);
     auto eigen_in = framework::EigenVector<T>::Flatten(*in);
diff --git a/paddle/operators/sgd_op.h b/paddle/operators/sgd_op.h
index b54a7864b056b332582b7be1fec0e86c571d9717..8422b622ee54ba76fb98b7dacfa9618031c1c88c 100644
--- a/paddle/operators/sgd_op.h
+++ b/paddle/operators/sgd_op.h
@@ -31,7 +31,7 @@ class SGDOpKernel : public framework::OpKernel {
     auto param = ctx.Input<Tensor>("param");
     auto grad = ctx.Input<Tensor>("grad");
     auto param_out = ctx.Output<Tensor>("param_out");
-    float lr = ctx.op().GetAttr<float>("learning_rate");
+    float lr = ctx.GetAttr<float>("learning_rate");
 
     param_out->mutable_data<T>(ctx.GetPlace());
 
diff --git a/paddle/operators/uniform_random_op.cc b/paddle/operators/uniform_random_op.cc
index dbff2a1365fbd38f243a1a756f5ab1fe61f09430..2d943c4508490d25a8747330c92c24c384bd0232 100644
--- a/paddle/operators/uniform_random_op.cc
+++ b/paddle/operators/uniform_random_op.cc
@@ -26,16 +26,15 @@ class CPUUniformRandomKernel : public framework::OpKernel {
   void Compute(const framework::ExecutionContext& context) const override {
     auto* tensor = context.Output<framework::Tensor>("Out");
     T* data = tensor->mutable_data<T>(context.GetPlace());
-    unsigned int seed =
-        static_cast<unsigned int>(context.op().GetAttr<int>("seed"));
+    unsigned int seed = static_cast<unsigned int>(context.GetAttr<int>("seed"));
     std::minstd_rand engine;
     if (seed == 0) {
       seed = std::random_device()();
     }
     engine.seed(seed);
     std::uniform_real_distribution<T> dist(
-        static_cast<T>(context.op().GetAttr<float>("min")),
-        static_cast<T>(context.op().GetAttr<float>("max")));
+        static_cast<T>(context.GetAttr<float>("min")),
+        static_cast<T>(context.GetAttr<float>("max")));
     ssize_t size = framework::product(tensor->dims());
     for (ssize_t i = 0; i < size; ++i) {
       data[i] = dist(engine);
diff --git a/paddle/operators/uniform_random_op.cu b/paddle/operators/uniform_random_op.cu
index fc8397f134f421c89d5855d0d00e9363ec6ea58c..df993c07794b0b2408e4edc8a45fae9a17aef01c 100644
--- a/paddle/operators/uniform_random_op.cu
+++ b/paddle/operators/uniform_random_op.cu
@@ -45,14 +45,13 @@ class GPUUniformRandomKernel : public framework::OpKernel {
   void Compute(const framework::ExecutionContext& context) const override {
     auto* tensor = context.Output<framework::Tensor>("Out");
     T* data = tensor->mutable_data<T>(context.GetPlace());
-    unsigned int seed =
-        static_cast<unsigned int>(context.op().GetAttr<int>("seed"));
+    unsigned int seed = static_cast<unsigned int>(context.GetAttr<int>("seed"));
     if (seed == 0) {
       std::random_device rd;
       seed = rd();
     }
-    T min = static_cast<T>(context.op().GetAttr<float>("min"));
-    T max = static_cast<T>(context.op().GetAttr<float>("max"));
+    T min = static_cast<T>(context.GetAttr<float>("min"));
+    T max = static_cast<T>(context.GetAttr<float>("max"));
     thrust::counting_iterator<unsigned int> index_sequence_begin(0);
     ssize_t N = framework::product(tensor->dims());
     thrust::transform(index_sequence_begin, index_sequence_begin + N,